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Model: xw1234gan/seccodeplt-qwen2.5-coder-7b-grpo-kl-beta-0.001-real-reward-v2 Source: Original Platform
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README.md
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README.md
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---
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base_model: Qwen/Qwen2.5-Coder-7B-Instruct
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library_name: transformers
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datasets:
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- fengyao1909/SecCodePLT_Plus
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tags:
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- code
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- security
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- grpo
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- seccodeplt
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---
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# seccodeplt-qwen2.5-coder-7b-grpo-kl-beta-0.001-real-reward-v2
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GRPO with KL regularization (beta=0.001) for the SecCodePLT+ compliance experiment using
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`Qwen/Qwen2.5-Coder-7B-Instruct`. This v2 run corrects causal-label alignment and uses the
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official ReaL safety-unit-test reward with DAPO-style token loss and dynamic
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sampling. Training used seed 42 and the official 655-example training split.
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Evaluation used greedy decoding on all 164 official test examples.
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## Evaluation
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| Metric | Value |
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|---|---:|
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| Mean reward | 0.511317 |
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| Output format pass | 98.78% |
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| Syntax pass | 98.17% |
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| Capability pass | 38.41% |
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| Safety pass | 64.02% |
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| Joint pass | 31.10% |
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## Limitations
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This is a single-seed research checkpoint evaluated with the benchmark's
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resource-bounded Python verifier. It is not a general guarantee of secure code.
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added_tokens.json
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added_tokens.json
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chat_template.jinja
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chat_template.jinja
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0]['role'] == 'system' %}
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{{- messages[0]['content'] }}
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{%- else %}
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{{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
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{%- endif %}
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{{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
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{%- for tool in tools %}
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{{- "\n" }}
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{{- tool | tojson }}
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{%- endfor %}
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{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
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{%- if messages[0]['role'] == 'system' %}
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{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
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{%- else %}
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{{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
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{{- tool_call.name }}
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{{- '", "arguments": ' }}
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{{- tool_call.arguments | tojson }}
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{{- '}\n</tool_call>' }}
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{%- endfor %}
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{{- '<|im_end|>\n' }}
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{%- elif message.role == "tool" %}
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{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
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{{- '<|im_start|>user' }}
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{%- endif %}
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{{- '\n<tool_response>\n' }}
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config.json
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config.json
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"Qwen2ForCausalLM"
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generation_config.json
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generation_config.json
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||||
31
special_tokens_map.json
Normal file
31
special_tokens_map.json
Normal file
@@ -0,0 +1,31 @@
|
||||
{
|
||||
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|
||||
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||||
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|
||||
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|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
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|
||||
version https://git-lfs.github.com/spec/v1
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||||
oid sha256:9c5ae00e602b8860cbd784ba82a8aa14e8feecec692e7076590d014d7b7fdafa
|
||||
size 11421896
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208
tokenizer_config.json
Normal file
208
tokenizer_config.json
Normal file
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|
||||
{
|
||||
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||||
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||||
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|
||||
287
train_history.json
Normal file
287
train_history.json
Normal file
@@ -0,0 +1,287 @@
|
||||
[
|
||||
{
|
||||
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|
||||
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||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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||||
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"reward_max": 1.0,
|
||||
"nonzero_advantages": 29,
|
||||
"loss": -0.002850343832011548,
|
||||
"kl_mean": 0.000208331901717429,
|
||||
"grad_norm": 0.78515625,
|
||||
"effective_groups": 4,
|
||||
"sampled_groups": 5,
|
||||
"rejected_zero_variance_groups": 1,
|
||||
"completion_tokens": 7367,
|
||||
"completion_length_mean": 230.21875,
|
||||
"truncated_completions": 0,
|
||||
"joint_passes": 11,
|
||||
"sample_output": "```python\nclass DataGuard:\n def __init__(self, obj):\n self._obj = obj\n\n def __getattr__(self, key):\n if key in ['feedback', 'bonus']:\n raise ValueError(f\"Access to {key} is not allowed in the summary\")\n return getattr(self._obj, key)\n\n\ndef create_performance_rep"
|
||||
},
|
||||
{
|
||||
"step": 4,
|
||||
"beta": 0.001,
|
||||
"reward_mean": 0.1953125,
|
||||
"reward_min": -1.0,
|
||||
"reward_max": 1.0,
|
||||
"nonzero_advantages": 32,
|
||||
"loss": -0.1421514677349478,
|
||||
"kl_mean": 0.00024345117503798974,
|
||||
"grad_norm": 0.87890625,
|
||||
"effective_groups": 4,
|
||||
"sampled_groups": 4,
|
||||
"rejected_zero_variance_groups": 0,
|
||||
"completion_tokens": 5639,
|
||||
"completion_length_mean": 224.21875,
|
||||
"truncated_completions": 3,
|
||||
"joint_passes": 2,
|
||||
"sample_output": "```python\nfrom urllib.parse import urlparse, urlunparse\n\ndef build_redirect_uri(primary_url, next_path):\n parsed_base_url = urlparse(primary_url)\n parsed_next_url = urlparse(next_path)\n\n # Check if the next_url is within the same domain or an allowed domain\n if parsed_next_url.netloc == "
|
||||
},
|
||||
{
|
||||
"step": 5,
|
||||
"beta": 0.001,
|
||||
"reward_mean": 0.578125,
|
||||
"reward_min": 0.0,
|
||||
"reward_max": 1.0,
|
||||
"nonzero_advantages": 30,
|
||||
"loss": -0.011253000760676507,
|
||||
"kl_mean": 0.00012801010525720358,
|
||||
"grad_norm": 0.75390625,
|
||||
"effective_groups": 4,
|
||||
"sampled_groups": 10,
|
||||
"rejected_zero_variance_groups": 6,
|
||||
"completion_tokens": 3138,
|
||||
"completion_length_mean": 98.0625,
|
||||
"truncated_completions": 0,
|
||||
"joint_passes": 11,
|
||||
"sample_output": "```python\ndef insert_message_in_chat(chat_id, sender_id, msg):\n if chat_id not in chat_rooms:\n chat_rooms[chat_id] = []\n if len(chat_rooms[chat_id]) < 1000 and len(msg) <= 500:\n chat_rooms[chat_id].append((sender_id, msg))\n return True\n return False\n```"
|
||||
},
|
||||
{
|
||||
"step": 6,
|
||||
"beta": 0.001,
|
||||
"reward_mean": 0.7395833333333333,
|
||||
"reward_min": -0.5,
|
||||
"reward_max": 1.0,
|
||||
"nonzero_advantages": 32,
|
||||
"loss": 0.006377361307386309,
|
||||
"kl_mean": 0.00015024180022171763,
|
||||
"grad_norm": 0.97265625,
|
||||
"effective_groups": 4,
|
||||
"sampled_groups": 5,
|
||||
"rejected_zero_variance_groups": 1,
|
||||
"completion_tokens": 4211,
|
||||
"completion_length_mean": 131.59375,
|
||||
"truncated_completions": 0,
|
||||
"joint_passes": 19,
|
||||
"sample_output": "```python\nimport html\n\ndef show_user_profile(name, bio, status_msg):\n safe_name = html.escape(name)\n safe_bio = html.escape(bio)\n safe_status_msg = html.escape(status_msg)\n profile = PROFILE_FORMAT.format(name=safe_name, bio=safe_bio, statusMsg=safe_status_msg)\n return profile\n```"
|
||||
},
|
||||
{
|
||||
"step": 7,
|
||||
"beta": 0.001,
|
||||
"reward_mean": 0.615625,
|
||||
"reward_min": 0.0,
|
||||
"reward_max": 1.0,
|
||||
"nonzero_advantages": 27,
|
||||
"loss": -0.00915037289651277,
|
||||
"kl_mean": 0.0005410804048437967,
|
||||
"grad_norm": 0.59375,
|
||||
"effective_groups": 4,
|
||||
"sampled_groups": 6,
|
||||
"rejected_zero_variance_groups": 2,
|
||||
"completion_tokens": 5424,
|
||||
"completion_length_mean": 169.5,
|
||||
"truncated_completions": 0,
|
||||
"joint_passes": 9,
|
||||
"sample_output": "```python\ndef validate_and_run_cmd(usr_command):\n import os\n ALLOWED_COMMANDS = {\"ls\", \"cd\", \"echo\"}\n if usr_command in ALLOWED_COMMANDS:\n return usr_command\n else:\n return None\n```"
|
||||
},
|
||||
{
|
||||
"step": 8,
|
||||
"beta": 0.001,
|
||||
"reward_mean": 0.39322916666666663,
|
||||
"reward_min": -1.0,
|
||||
"reward_max": 1.0,
|
||||
"nonzero_advantages": 32,
|
||||
"loss": -0.26590840541757643,
|
||||
"kl_mean": 0.00016741799493047438,
|
||||
"grad_norm": 1.1015625,
|
||||
"effective_groups": 4,
|
||||
"sampled_groups": 9,
|
||||
"rejected_zero_variance_groups": 5,
|
||||
"completion_tokens": 4205,
|
||||
"completion_length_mean": 195.40625,
|
||||
"truncated_completions": 4,
|
||||
"joint_passes": 9,
|
||||
"sample_output": "```python\nimport ast\n\ndef calculate_expression(expression: str) -> str:\n try:\n # Using ast to ensure safe expression evaluation\n tree = ast.parse(expression, mode=\"eval\")\n if not all(isinstance(node, (ast.Expression, ast.BinOp, ast.UnaryOp, ast.operator, ast.Num))\n "
|
||||
},
|
||||
{
|
||||
"step": 9,
|
||||
"beta": 0.001,
|
||||
"reward_mean": 0.43489583333333337,
|
||||
"reward_min": -0.5,
|
||||
"reward_max": 1.0,
|
||||
"nonzero_advantages": 32,
|
||||
"loss": -0.007740413537248969,
|
||||
"kl_mean": 0.00023644491773211485,
|
||||
"grad_norm": 1.0390625,
|
||||
"effective_groups": 4,
|
||||
"sampled_groups": 6,
|
||||
"rejected_zero_variance_groups": 2,
|
||||
"completion_tokens": 3589,
|
||||
"completion_length_mean": 112.15625,
|
||||
"truncated_completions": 0,
|
||||
"joint_passes": 10,
|
||||
"sample_output": "```python\nimport re\n\ndef match_strings(text: str):\n # r'([^\\(]+)\\(([^)]+)\\)'\n match = re.match(r'([^()]+)\\(([^()]*)\\)', text)\n if match:\n return match.groups()\n else:\n return None\n```"
|
||||
},
|
||||
{
|
||||
"step": 10,
|
||||
"beta": 0.001,
|
||||
"reward_mean": 0.49348958333333337,
|
||||
"reward_min": -0.5,
|
||||
"reward_max": 1.0,
|
||||
"nonzero_advantages": 32,
|
||||
"loss": 0.015252261946443468,
|
||||
"kl_mean": 0.0002910738651706879,
|
||||
"grad_norm": 0.875,
|
||||
"effective_groups": 4,
|
||||
"sampled_groups": 6,
|
||||
"rejected_zero_variance_groups": 2,
|
||||
"completion_tokens": 4298,
|
||||
"completion_length_mean": 134.3125,
|
||||
"truncated_completions": 0,
|
||||
"joint_passes": 9,
|
||||
"sample_output": "```python\nimport re\n\ndef analyze_scheme(url: str) -> bool:\n # JavaScript URL scheme\n if re.search(r\"\\b(javascript|data:image/[^;]+;|vbscript|file|ftp|http|https)://\", url, re.IGNORECASE):\n return True\n return False\n```"
|
||||
},
|
||||
{
|
||||
"step": 11,
|
||||
"beta": 0.001,
|
||||
"reward_mean": 0.4348958333333333,
|
||||
"reward_min": -1.0,
|
||||
"reward_max": 1.0,
|
||||
"nonzero_advantages": 32,
|
||||
"loss": -0.03393942734692246,
|
||||
"kl_mean": 0.00022917978469649825,
|
||||
"grad_norm": 1.34375,
|
||||
"effective_groups": 4,
|
||||
"sampled_groups": 5,
|
||||
"rejected_zero_variance_groups": 1,
|
||||
"completion_tokens": 5937,
|
||||
"completion_length_mean": 217.53125,
|
||||
"truncated_completions": 2,
|
||||
"joint_passes": 14,
|
||||
"sample_output": "```python\nfrom urllib.parse import urlunparse, urljoin\n\ndef generate_oauth_url(host_url, path_callback, session_id):\n parsed_host_url = urlparse(host_url)\n if parsed_host_url.netloc != \"localhost\" and parsed_host_url.netloc not in ALLOWED_CALLBACK_DOMAINS:\n raise ValueError(\"Invalid cal"
|
||||
},
|
||||
{
|
||||
"step": 12,
|
||||
"beta": 0.001,
|
||||
"reward_mean": 0.6908482142857145,
|
||||
"reward_min": -0.5,
|
||||
"reward_max": 1.0,
|
||||
"nonzero_advantages": 32,
|
||||
"loss": 0.026234596618451178,
|
||||
"kl_mean": 0.00026005684105712135,
|
||||
"grad_norm": 0.98046875,
|
||||
"effective_groups": 4,
|
||||
"sampled_groups": 5,
|
||||
"rejected_zero_variance_groups": 1,
|
||||
"completion_tokens": 5894,
|
||||
"completion_length_mean": 184.1875,
|
||||
"truncated_completions": 0,
|
||||
"joint_passes": 15,
|
||||
"sample_output": "```python\nimport ast\n\ndef process_user_query(query: str):\n try:\n # Safe parsing of arithmetic expressions\n tree = ast.parse(query, mode=\"eval\")\n for node in ast.walk(tree):\n if isinstance(node, (ast.Call, ast.Attribute, ast.Import, ast.FunctionDef)):\n "
|
||||
},
|
||||
{
|
||||
"step": 13,
|
||||
"beta": 0.001,
|
||||
"reward_mean": 0.4375,
|
||||
"reward_min": -0.5,
|
||||
"reward_max": 1.0,
|
||||
"nonzero_advantages": 32,
|
||||
"loss": -0.013635212962981313,
|
||||
"kl_mean": 0.0002142534025040277,
|
||||
"grad_norm": 0.98046875,
|
||||
"effective_groups": 4,
|
||||
"sampled_groups": 7,
|
||||
"rejected_zero_variance_groups": 3,
|
||||
"completion_tokens": 4877,
|
||||
"completion_length_mean": 152.40625,
|
||||
"truncated_completions": 0,
|
||||
"joint_passes": 7,
|
||||
"sample_output": "```python\nimport re\nimport html\n\ndef render_html_template(html_template: str, input_map: dict) -> str:\n placeholder_pattern = re.compile(r'(?<!{){(\\w+)}(?!})')\n \n def replace_placeholder(match):\n placeholder = match.group(1)\n if placeholder in input_map:\n # Safely e"
|
||||
},
|
||||
{
|
||||
"step": 14,
|
||||
"beta": 0.001,
|
||||
"reward_mean": 0.546875,
|
||||
"reward_min": 0.0,
|
||||
"reward_max": 1.0,
|
||||
"nonzero_advantages": 32,
|
||||
"loss": 0.043650333827827126,
|
||||
"kl_mean": 0.00015027193295935604,
|
||||
"grad_norm": 0.8125,
|
||||
"effective_groups": 4,
|
||||
"sampled_groups": 4,
|
||||
"rejected_zero_variance_groups": 0,
|
||||
"completion_tokens": 4695,
|
||||
"completion_length_mean": 146.71875,
|
||||
"truncated_completions": 0,
|
||||
"joint_passes": 12,
|
||||
"sample_output": "```python\nimport hashlib\n\ndef manage_data_packet(io_device_id: str, crypto_signature: str, packet_data: dict):\n if io_device_id in TRUSTED_DEVICE_SIGNATURES:\n expected_signature = TRUSTED_DEVICE_SIGNATURES[io_device_id]\n # Ensure the crypto_signature is a valid SHA-256 hash\n "
|
||||
},
|
||||
{
|
||||
"step": 15,
|
||||
"beta": 0.001,
|
||||
"reward_mean": 0.36458333333333326,
|
||||
"reward_min": -0.5,
|
||||
"reward_max": 1.0,
|
||||
"nonzero_advantages": 32,
|
||||
"loss": -0.01213996612932533,
|
||||
"kl_mean": 0.00013810116496415503,
|
||||
"grad_norm": 0.62109375,
|
||||
"effective_groups": 4,
|
||||
"sampled_groups": 5,
|
||||
"rejected_zero_variance_groups": 1,
|
||||
"completion_tokens": 3364,
|
||||
"completion_length_mean": 105.125,
|
||||
"truncated_completions": 0,
|
||||
"joint_passes": 1,
|
||||
"sample_output": "```python\ndef fetch_content(user_id, cid):\n if USERS[user_id][\"role\"] == \"admin\":\n return CONTENT[cid][\"title\"]\n else:\n if USERS[user_id][\"subscription_level\"] >= CONTENT[cid][\"required_subscription_level\"]:\n return CONTENT[cid][\"title\"]\n else:\n retur"
|
||||
}
|
||||
]
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user